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An Open-Source Platform for Human Pose Estimation and Tracking Using a Heterogeneous Multi-Sensor System.

Ashok Kumar Patil¹, Adithya Balasubramanyam¹, Jae Yeong Ryu¹

¹Virtual Environments Lab, Graduate School of Advanced Imaging Science, Multimedia and Film, Chung-Ang University, Seoul 06974, Korea.

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|April 3, 2021

Summary

This summary is machine-generated.

This study introduces a real-time 3D human pose tracking system using lidar and inertial sensors. The fused sensor data improves accuracy and overcomes limitations of single-sensor systems.

Keywords:

detection heterogeneous sensor human pose estimation inertial sensor lidar sensor multi-sensor sensor fusion tracking

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Area of Science:

Robotics
Computer Vision
Human-Computer Interaction

Background:

Real-time human pose estimation and tracking are crucial for various applications.
Single sensor types like inertial sensors suffer from drift, impacting long-term accuracy.
Combining heterogeneous sensors offers potential for enhanced human motion tracking.

Purpose of the Study:

To propose and develop a novel human motion tracking system for real-time 3D human pose estimation.
To fuse data from lidar and inertial sensors to improve tracking accuracy and robustness.
To enable reconstruction of estimated human motion data onto a virtual 3D avatar.

Main Methods:

Developed a human motion tracking system integrating lidar and inertial sensors.
Implemented sensor fusion algorithms to combine data from heterogeneous sources.
Utilized open-source platform APIs for system development.
Experimental validation of the proposed system's performance.

Main Results:

The system accurately estimates 3D human pose, including height, skeletal parameters, position, and orientation in real-time.
Data fusion from lidar and inertial sensors effectively mitigated single-sensor drift issues.
Reconstruction of estimated human motion onto a virtual 3D avatar was successfully demonstrated.
Experimental results showed good agreement with existing multi-sensor systems.

Conclusions:

The proposed lidar-inertial sensor fusion system provides accurate and robust real-time 3D human pose tracking.
This approach overcomes the limitations of single-sensor systems, particularly sensor drift.
The system has potential applications in areas requiring precise human motion analysis and virtual representation.